Key imperatives in creating a robust customer behaviour strategy

Today’s always-on customer has a shorter attention span than a goldfish. The emergence of user-friendly technology and split-second access to information have given birth to a breed of smart, know-it-all customers. With so many options available just at a swipe of the screen, customer behaviour is in a state of flux. How do brand marketers address this?

Digitisation and capturing customer data has opened the doors to new opportunities for brands to understand their customers and offer personalised experiences. Brands now have the power to build a 360-degree view of the customer through online and offline behaviour.

A recent study reveals 81 per cent of marketers still report challenges in achieving this view. Many take the path of collecting and integrating information about their customers through CRM and customer service channels, mobile applications, web sites, social media, third party data and IVR.

Most of these data consolidation projects end up as multi-year programs worth millions of dollars without realising the benefit. Leveraging insights across various marketing channels such as campaigns and personalisation becomes secondary in such projects. Let us explore an alternative approach.

Complement your ‘customer first strategy’ with ‘reap the benefit as you go’ implementation strategy

While most brands are right with their ‘customer first’ strategy, they are often over-ambitious during its implementation. In this scenario, a 360-degree customer view could provide the brand a competitive advantage, but delay in reaching there is an opportunity lost.

Alternatively, the marketer should look at building the customer view incrementally and ‘reap benefits as you build it’, to stay ahead of the curve. This is typically referred as a ‘use case driven’ approach. That is, identify use cases as you onboard incremental data and execute them without waiting for the entire customer data.

Today’s technology and processes allow building a system with the flexibility of adding features without affecting the overall quality or stability. There are a number of success stories confirming this fact, including the largest retailer and cloud service provider Amazon which does close to 50 million releases per year, which is one release per second!

Begin with a solid foundation (base platform)

The top challenge in building a single customer view lies in the technology to build, integrate and access customer information, within an enterprise. This is primarily due to the usage of traditional data technologies in the new age and slow adoption of marketing technologies as many in the field would accept.

True, most brands have a customer relationship management (CRM) solution in place. However, the quality of customer data, duplicate customer information, and the inability to scale for the digital era and store unstructured or semi-structured information pose challenges. An eMarketer survey shows that more than 50 per cent of marketers admit that they don’t have the technology or data available for any personalised marketing.

So the CMO should make the scalable base platform with all the existing data available (transactional information) before attempting the complex digital footprint data.

Leverage existing data

Though there is a push to use customer data for personalised marketing, the adoption at basic level is not encouraging. An eMarketer survey early this year shows only 23 per cent of the retailers in the US are using purchase information for recommendations.

This is an opportunity. Brands can immediately start leveraging available information to execute use cases such as personalised offers at a basic level without waiting for more data, and even achieve some ROI. The foundation data store should have a sound view of customers including their purchase history. This information is critical to identify the high-value customers and their product affinity.

The next step for the CMO is to utilise this information wisely to create focused marketing campaigns targeted at high-value customers with offers based on past transactions. This is the first use case brands can implement while starting from ground zero for a personalised customer experience. Organisations such as Netflix and Spotify use the product purchase history to effectively target customers.

Although the marketer should gun for a 360-degree customer view, he should build it gradually. Any data added to the store could be the indicators of:

Customer experience: How satisfied the customer is with the product or services (loyalty or potential churn)

Customer intent: Purchase intent for products and services, which can be converted

Here are some potential data sources that can be added and the corresponding use cases that can be implemented:

Customer service data

This would be available in its most basic form from the customer service centre. This data can be added to the data store and can be used to predict customer churn based on the number of complaints or feedback received. For instance, 62 per cent of companies say they will use AI by 2018 and one of the most prominent use case for telecom is churn prediction.

This kind of information also enables reaching out to customers proactively through campaigns or one-on-one with offers to reduce the churn probability. Vodafone uses this information to save retention costs

Digital data

CMOs can integrate customer behaviour from their websites by leveraging web analytics and tag management solutions to understand customer intent. Digital behaviour can help create personalised marketing messages through e-mail campaigns or personalised ads while customers are on a particular website. This empowers brand marketers to take proactive steps to avoid unpleasant customer experiences in the future. This is the most known use of personalisation and companies such as Amazon and Netflix are pioneers in this space.

Mobile data

This is the next target for integration with app usage behaviour and location awareness. It can be used to get personalised messages and location-aware offers through existing integration with campaign systems. The customer’s browse history can also help the marketer trigger relevant offers basis the customer intent. Success stories of OLX and Bose point to its effective use.

Social data

‘Go social’ could be another approach to understand customer preferences such as likes, dislikes and social circle along with the influencer set. Marketers can explore social media channels to augment meaningful customer experiences. Based on the sentiment data about the products and services, the original churn prediction can be improved. According to a Sociable Labs study, 75 per cent of shoppers who read ‘comments’ about a product claim to have clicked on the link in their friends’ Facebook posts, which led them directly to the product page or a retailer’s website. Fifty-three per cent of these shoppers finally made a purchase.

Physical behaviour data

Data on customers’ physical behaviour can be captured by integrating IoT or mobile devices. For instance, security and customer devices can capture usage patterns and provide information such as energy patterns and usage frequency to trigger recommendations for usage and proactive offers.

Finally, get to a 360-degree customer view

This is critical for stitching the missing pieces together and creating a seamless customer journey. Brands can implement various use cases to build a holistic journey that runs across online and offline channels. This will help them optimise purchase intent and churn prediction. Besides, third party sources can help augment customer information, leading to better efficiency.

While incrementally building customer view helps recover RoI rather than waiting for the final view, the key differentiator is how effectively you combine these journeys to derive unique insights. Brands such as Nordstrom are using this effectively to deliver unique customer experiences basis the journey built over various sources.

In this era of digital deluge, gleaning relevant customer insights from the ocean of Big Data, that too incrementally, holds the key to crafting powerful brand marketing campaigns for target customers. And the sooner marketers realise this, the better.

Suresh Sankaran is Director, Technology, SapientRazorfish.

COMMENT NOW